Social media plays a pivotal role in global discussions, including on climate change. The variety of opinions expressed range from supportive to oppositional, with some instances of hate speech. Recognizing the importance of understanding these varied perspectives, the 7th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE) at EACL 2024 hosted a shared task focused on detecting stances and hate speech in climate activism-related tweets. This task was divided into three subtasks: subtasks A and B concentrated on identifying hate speech and its targets, while subtask C focused on stance detection. Participants'' performance was evaluated using the macro F1-score. With over 100 teams participating, the highest F1 scores achieved were 91.44 in subtask C, 78.58 in subtask B, and 74.83 in subtask A. This paper details the methodologies of 24 teams that submitted their results to the competition''s leaderboard.

Stance and Hate Event Detection in Tweets Related to Climate Activism - Shared Task at CASE 2024

Causal (a cause-effect relationship between two arguments) has become integral to various NLP domains such as question answering, summarization, and event prediction. To understand causality in detail, Event Causality Identification with Causal News Corpus (CASE-2022) has organized shared tasks. This paper defines our participation in Subtask 1, which focuses on classifying event causality. We used sentence-level augmentation based on contextualized word embeddings of distillBERT to construct new data. This data was then trained using two approaches. The first technique used the DeBERTa language model, and the second used the RoBERTa language model in combination with cross-attention. We obtained the second-best F1 score (0.8610) in the competition with the Contextually Augmented DeBERTa model.

ARGUABLY @ Causal News Corpus 2022: Contextually Augmented Language Models for Event Causality Identification

With the increase in the use of social media, people have become more outspoken and are using platforms like Reddit, Facebook, and Twitter to express their views and share the medical challenges they are facing. This data is a valuable source of medical insight and is often used for healthcare research. This paper describes our participation in Task 1a, 2a, 2b, 3, 5, 6, 7, and 9 organized by SMM4H 2022. We have proposed two transformer-based approaches to handle the classification tasks. The first approach is fine-tuning single language models. The second approach is ensembling the results of BERT, RoBERTa, and ERNIE 2.0.

Classification of HealthRelated Tweets Using Ensemble, Zero-Shot andFine-Tuned Language Model

[**Teleport to Gather**](https://app.gather.town/app/XDzSQW1b0mpTTAYr/EACL2024?spawnToken=qPtfN1icQ3aWE7S-_yMW) Nowadays, the unprecedented quantity of easily accessible data on social, political, and economic processes offers ground-breaking potential in guiding data-driven analysis in social and human sciences and in driving informed policy-making processes. Governments, multilateral organizations, and local and global NGOs present an increasing demand for high-quality information about a wide variety of events ranging from political violence, environmental disasters, and conflict, to international economic and health crises (Coleman et al. 2014; Porta and Diani, 2015) to prevent or resolve conflicts, provide relief for those that are afflicted, or improve the lives of and protect citizens in a variety of ways. Citizen actions against the COVID measures in the period 2020-2022 and the Russia – Ukraine war are only two examples where event-centered data can contribute to better understanding of real-life situations. Finally, these efforts respond to “growing public interest in up-to-date information on crowds” as well. [**Read more**](https://emw.ku.edu.tr/case-2024/) **Program Overview** 
09:00 - 09:10 Opening Remarks 
09:10 - 10:10 Event Extraction, approaches and resources 
10:10 - 10:30 Large Language Models for Event Extraction, Part I 
10:30 - 11:00 Coffee Break 
11:00 - 12:00 Large Language Models for Event Extraction, Part II 
12:00 - 12:40 Cllimate Activism Hate and Stance Event Detection Shared Task 
12:40 - 14:00 Lunch Break 
14:00 - 14:45 Hate Speech in Turkish and Arabic Tweets (HSD-2LANG) 
14:45 - 15:30 Multimodal Hate Speech Event Detection 
15:30 - 16:00 Coffee Break 
16:00 - 17:00 Poster session 
17:00 - 17:20 Closing remarks

W11: The 7th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE)

workshop paper

Welcome to the 18th Conference of the European Chapter of the Association for Computational Linguistics (EACL). Continuing its mission of expanding and involving the science community of all European countries, EACL has selected the Malta community for the 18th EACL. Considering the importance of physical interaction among researchers, the conference will be held at the Hotel Radisson Blu, St. Julians, in Malta, from 17 to 22 of March, 2024. The conference will also feature the possibility to participate virtually. As the flagship European conference in the field of computational linguistics, EACL welcomes European and international researchers covering a broad spectrum of research areas that are concerned with computational approaches to natural language. 
#### [Conference Handbook](https://drive.google.com/file/d/13Wn38q0yev6U3RTgnf4Tn5T9GuAuZ-xW/view?usp=sharing) *downloadable*

To access the EACL 2024 event page you need to register [**here**](https://acl.swoogo.com/EACL2024). 

Please register!

EACL 2024

As the flagship European conference in the field of computational linguistics, EACL welcomes European and international researchers covering a broad spectrum of research areas that are concerned with computational approaches to natural language.

**Chair:** Ali Hürriyetoğlu **Organizers:** Ali Hürriyetoğlu, Hristo Tanev, Vanni Zavarella, Tadashi Nomoto, Benjamin Radford, Milena Slavcheva, and Erdem Yörük 
**Invited speakers**: [J. Craig Jenkins](https://underline.io/speakers/212902-j.-craig-jenkins), [Scott Althaus](https://underline.io/speakers/212905-scott-althaus) and [Thien Huu Nguyen](https://underline.io/speakers/40729-thien-nguyen)
 Please visit our [**website**](https://emw.ku.edu.tr/case-2022/) for more information and detailed schedule. 
**Rocket channel for this workshop:** https://emnlp2022.rocket.chat/channel/workshop-1-case

 [**Live Session Recording - Day 1**](https://us06web.zoom.us/rec/play/7lXvGAHeFunqc7drItCsNDX8r5dOT-k28zCHHEELV9EytnckOe0wj0GBGitxhcuV4aKlkyTn7UxnsRq4.WDecGUCgdz2bEdW-?autoplay=true&startTime=1670386043000)
 
[**Live Session Recording - Day 2**](https://us06web.zoom.us/rec/play/DuXvqjg035NP1dnOgcQRop3wvW3c4bn_xrxLPineJpgI2Ra_3AKPM7GT1jI-hQlKTvKx4VJAwKjwxrYz.UJa5WCrjg5M2GMLX?autoplay=true&startTime=1670471578000)

W1 (CASE) The 5th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text 

## Welcome to EMNLP 2022!
I am delighted to welcome you to EMNLP 2022! I believe this conference has been complicated beyond any precedent. Over the past year, it’s been thrilling to see the organization team approach each new puzzle with creativity and enthusiasm. We hope that those participating in Abu Dhabi as well as those joining remotely will leave the conference feeling newly inspired by the program and newly connected to our ever-growing community. Following EMNLP 2021 and major NLP conferences since, EMNLP 2022 is “hybrid,” serving both virtual and in-person participants.

Our key innovations for EMNLP 2022 include:

* EMNLP 2022 is “hybrid” in a second sense, as well: we allowed both direct and rolling review paper submissions, building on the pilot experiment of EMNLP 2021, which considered a small number of ARR submissions. 
* Familiar from NAACL but new to EMNLP, we’ve added an industry track.
* During the conference, “portals” will link virtual poster sessions to in-person conference participants during poster sessions each day.
* The first ACL-family conference in the United Arab Emirates.

 *Message from Noah A. Smith, University of Washington and Allen Institute for AI, Seattle, Washington, USA* 
***EMNLP 2022 General Chair***
 
[![](https://assets.underline.io/uploads/markdown_image/1/image/9eec7d4a287ee18c278b08229290aa83.png)](https://drive.google.com/file/d/1OlPv6QBeo62VVTughj2jkiLeyHd1WnUt/view)
 
[![](https://assets.underline.io/uploads/markdown_image/1/image/a3db7a768409f05192210d98601edb25.png)](https://emnlp2022.rocket.chat/)

To access this site you need to register. Please register [here](https://2022.emnlp.org/registration/).

Register here

EMNLP 2022

Welcome!
EMNLP 2022 will take place in Abu Dhabi from December 7th to December 11th, 2022. And it will be held in hybrid mode, both online and offline.

Click on the Live Session Recording to view the session 
[Live Session Recording Part 1](https://us06web.zoom.us/rec/share/qHEG09EELYlte_7R9OUbNrESzVkcdTGVVl3jLi5YPzAMxZX552x7VHCVIX6dL0BO.nlEJhftSpzZDocq0?startTime=1665960992000) [Live Session Recording Part 2](https://us06web.zoom.us/rec/share/qHEG09EELYlte_7R9OUbNrESzVkcdTGVVl3jLi5YPzAMxZX552x7VHCVIX6dL0BO.nlEJhftSpzZDocq0?startTime=1665985793000)
 
**Workshop overview:** The Social Media Mining for Health Applications (#SMM4H) workshop serves as a venue for bringing together researchers interested in automatic methods for the collection, extraction, representation, analysis, and validation of social media data (e.g., Twitter, Facebook) for health informatics. The 7th #SMM4H Workshop, co-located at Coling 2022, invites the submission of papers on original, unpublished research in all aspects at the intersection of social media mining and health. [**Read more.**](https://healthlanguageprocessing.org/smm4h-2022/)

W18 7th SMM4H Social Media Mining for Health Research and Applications - Workshop & Shared Task

[![](https://assets.underline.io/uploads/markdown_image/1/image/81a3c0317d24f663b49b996875024d45.png)](https://aclanthology.org/volumes/2022.coling-1/)



### THE CONFERENCE WE KNOW AND WE WANT.
**COLING**, the International Conference on Computational Linguistics, is one of the premier conferences for the natural language processing and computational linguistics.

First established in 1965, the biennial COLING conference is held in diverse parts of the globe and attracts participants from both top-ranked research centers and emerging countries. Today, the most important developments in our field are taking place not only in universities and academic research institutes but also in industrial research departments including tech-startups. COLING provides opportunities for all these communities to showcase their exciting discovery.

In fall of 2022, COLING will be held in Gyeongju in a hybrid format. All participants can either present at the venue site or join virtually. As more people get vaccinated, we are happy to provide safer environments for our colleagues. We believe that COLING 2022 will be one of the conferences, free from the pandemic. The hybrid format gives presenters and sponsors a valuable opportunity to promote their companies in both an online and in-person venue. For the first time in a long time, customers can interact with their sponsor's products first-hand. The online venue, too, gives sponsors the chance to network with those unable to attend the in-person session.

The hybrid format ultimately lends itself to greater exposure for our sponsors: COLING2022 will let you reach more potential partners and customers than ever before!

To gain access to this event page you are required to register. Find more information and pay the registration fee on event the organizer’s website **[https://coling2022.org/reg](https://coling2022.org/reg)**

COLING 2022

COLING, the International Conference on Computational Linguistics, is one of the premier conferences for the natural language processing and computational linguistics.

Guneet Singh Kohli

3

SHORT BIO

Presentations

Stance and Hate Event Detection in Tweets Related to Climate Activism - Shared Task at CASE 2024

ARGUABLY @ Causal News Corpus 2022: Contextually Augmented Language Models for Event Causality Identification

Classification of HealthRelated Tweets Using Ensemble, Zero-Shot andFine-Tuned Language Model

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